Wine-making system

Figure 1.3 is a system view of a wine-making process. In this system, there are two inputs (yeast and fruit), two outputs (percent alcohol and bouquet ), and a transform that is probably not known with certainty. 

Figure 1.3 General system theory view of a wine-making process.

Yeast and fruit are input variables in the wine-making process. In the case of yeast, the amount of a given strain could be varied, or the particular type of yeast could be varied. If the variation is of extent or quantity (e.g., the use of one ounce of yeast, or two ounces of yeast, or more) the variable is said to be a quantitative variable. If the variation is of type or quality (e.g., the use of Saccharomyces cerevisiae, or Saccharomyces ellipsoideus, or some other species) the variable is said to be a qualitative variable. Thus, yeast could be a qualitative variable (if the amount added is always the same, but the type of yeast is varied) or it could be a quantitative variable (if the type of yeast added is always the same, but the amount is varied). Similarly, fruit added in the wine-making process could be a qualitative variable or a quantitative variable. In the algebraic system, x is a quantitative variable. 

In the algebraic system discussed previously, x is a factor its value determines what the particular result y will be. Yeast and fruit are factors in the wine-making process the type and amount of each contributes to the alcohol content and flavor of the final product. 

Most systems have more than one response. The wine-making process introduced in Section 1.1 is an example. Percent alcohol and bouquet are two responses, but there are many additional responses associated with this system. Examples are the amount of carbon dioxide evolved, the extent of foaming, the heat produced during fermentation, the turbidity of the new wine, and the concentration of ketones in the final product. Just as factors can be classified into many dichotomous sets, so too can responses. One natural division is into important responses and unimportant responses, although the classification is not always straightforward. 

The criteria for classifying responses as important or unimportant are seldom based solely on the system itself, but rather are usually based on elements external to the system. For example, in the wine-making process, is percent alcohol an important or... 

Now let us consider the wine-making example and ask, Can we control temperature to produce a product of any exactly specified alcohol content (up to, say, 12%) The answer is that we probably cannot, and the reason is that the system behavior is initially not known with certainty. We know that some transform relating the alcohol content to the important factors must exist - that is. 

Just as there are many different types of systems, there are many different types of transforms. In the algebraic system pictured in Figure 1.2, the system transform is the algebraic relationship y = a + 2. In the wine-making system shown in Figure 1.3, the transform is the microbial colony that converts raw materials into a Hnished wine. Transforms in the chemical process industry are usually sets of chemical reactions that transform raw materials into finished products. 

Suppose we are interested in investigating the effect of fermentation temperature on the percent alcohol response of the wine-making system shown in Figure 1.6. We will assume that ambient pressure has very little effect on the system and that the small variations in response caused by this uncontrolled factor can be included in the residuals. Further, we can use the same type and quantity of yeast in all of our experiments so there will be no (or very little) variation in our results caused by the factor yeast . 

Completely randomized experimental design for determining the effect of temperature on a wine-making system. 

Some of these reactions and especially those involving anthocyanins, flavanols, and acetaldehyde (32-37), have been thoroughly studied in wine-like model systems (32-43). Numerous products have thus been obtained and partly characterized. Besides, some of them have recently been detected in red wines (38, 44). Two different groups of reactions were thus shown to occur in the course of wine making. 

In many systems the product inhibits the rate of growth. A classic example of this inhibition is in wine-making, where the fermentation of glucose to produce ethanol is inhibited by the product edianol. There are a number of different equations to account for inhibition one such rate law takes the form... 

Water purification They can be applied in deodorizing and de-coloring Applications in dififerent industrial field, like food and beverage, pharmaceutical, sugar-making, wine-making and also for super-pure water treatment system of electronic industry and aqueous filtration treatment. [9,71]... 

FTDI. The authors remarked that the instrumental advances and the associated open-source project recently reported can spread out the use of this universal detector for food analysis. Furthermore, the inherent portability of the C D system could make it an ideal instrument for on-site food testing. One example that combines creativity and the instrumental simplicity of this home-made conductivity detection is the analysis of monoalkyl carbonates in carbonated alcoholic beverages (sparkling wine, beer, and mixed drinks) [151]. By using two detectors, the authors not only demonstrated the presence of monoethyl carbonate (MFC) in the selected drinks but also proposed that the low pH values were responsible for the larger concentrations of MEC observed in lager beer and mixtures of rum and cola. In addition, the possibility to control not only a C D detector but also a series of valves using open-source software (Arduino) has been recently demonstrated [152]. 

---